MCP server and CLI for detecting, redacting, and auditing PHI before medical text is sent to AI agents.
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"charles-ree-phi-guard-mcp","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# phi-guard-mcp [](https://github.com/charlesree826/phi-guard-mcp/actions/workflows/ci.yml) [](https://github.com/charlesree826/phi-guard-mcp/releases) [](pyproject.toml) [](LICENSE) MCP server and CLI for detecting, redacting, and auditing PHI before medical text is sent to AI agents. `phi-guard-mcp` is healthcare AI safety infrastructure, not a clinical product. It is a local, rule-based guardrail that helps developers identify PHI-like identifiers in plain text, redact them with stable placeholders, and produce audit-friendly JSON before content reaches an AI agent or MCP workflow. Proof points for maintainers: - Synthetic benchmark with exact-match PHI finding evaluation. - Safe Harbor mapping audit fields for review workflows. - CI privacy gate that blocks PHI-like identifiers in maintained source and docs. - CLI, Python API, and MCP stdio tools sharing one stable JSON result model. Important scope limits: - Not for diagnosis, treatment, triage, medical advice, or medication recommendations. - Not a HIPAA compliance guarantee and not a substitute for legal, privacy, or security review. - Not an FDA-regulated clinical decision support or device software function. - Do not test with real patient records. The examples in this repo are synthetic. The project aligns its documentation vocabulary with HHS HIPAA de-identification concepts such as Safe Harbor and Expert Determination, while intentionally avoiding clinical decision support scope. See [HHS de-identification guidance](https://www.hhs.gov/hipaa/for-professionals/special-topics/de-identification/index.html), [FDA CDS guidance](https://www.fda.gov/regulatory-information/search-fda-guidance-d…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.